Who is this course best suited for?

<text variant="body1">This course is great for data engineers, analysts, cloud professionals, and anyone who wants to work in real-time analytics. It also works for IT people who want to move into cloud data roles and have hands-on experience with AWS.

What makes this course unique compared to others?

<text variant="body1">It goes beyond the basics by talking about more complex subjects like Redshift Lambda UDFs, serverless analytics, streaming with Kinesis and Flink, and event-driven workflows with Step Functions.

Will I get hands-on practice with AWS services?

<text variant="body1">For sure.The course features guided demos of Redshift walkthroughs, Athena + Glue integration, Kinesis scalability, and EventBridge workflows.This allows you to try applying AWS skills rather than simply learning about them.

How does this course stay relevant with evolving AWS services?

<text variant="body1">The modules are built around the main AWS services that most AWS data solutions use, such as Redshift, Glue, Kinesis, and Athena. These services change over time, but they stay the same at their core, which keeps your abilities up to date.

Is this course aligned with AWS certifications?

<text variant="body1">Yes. The course material is quite similar to the AWS Certified Data Engineer – Associate exam because it covers important services including Redshift, Glue, Kinesis, Athena, EMR, and Lake Formation. This course will not only help you get better at what you do in the real world, but it will also give you a strong base for passing the AWS certification exam.

How does this course support career growth?

<text variant="body1">There is a lot of need for people who know how to work with real-time data. Learning how to use AWS services will prepare you for jobs like Data Engineer, Cloud Engineer, and Analytics Specialist. These jobs are in fields that use streaming data and advanced analytics.

When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Real-Time Data Pipelines & Analytics on AWS

Real-Time Data Pipelines & Analytics on AWS

This course is part of AWS Certified Data Engineer Associate Exam Prep Specialization

Instructor: LearnKartS

Included with

Learn more

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Build real-time data pipelines with AWS tools like Kinesis, Glue, and Redshift.
Analyze and visualize streaming data using Athena, QuickSight, and OpenSearch.
Secure streams, scale clusters, and integrate Spark with AWS services.
Design production-ready pipelines for real-time business insights.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

10 assignments

Taught in English

91%

of learners achieved a positive career outcome

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

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Build your subject-matter expertise

This course is part of the AWS Certified Data Engineer Associate Exam Prep Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 2 modules in this course

In today’s digital economy, data shouldn’t stand still — neither should you. This course, Real-Time Data Pipelines & Analytics on AWS, provides you with the necessary skills to process streaming data and make it business-ready. Taught with a focus on actual use cases, you get hands-on practice with AWS’s most popular tools, including Amazon Redshift, Kinesis, Glue, Athena, EMR, QuickSight, OpenSearch, and more.

Whether you are new to cloud data engineering or have experience and want to learn the latest, this course offers a curated curriculum featuring practical demos, guided videos, and examples. You’ll discover ways to increase the performance of your Redshift cluster, secure Kinesis streams, and integrate Spark with various AWS services. You’ll also be able to design analytics pipelines that provide real-time results. By the time you are finished with this course, you will be able to build production-ready data pipelines that shine in today’s high-demand tech industry. Enroll now and begin your path towards the data engineer that every company is looking for. Disclaimer: AWS and Amazon Web Services are trademarks of Amazon.com, Inc. or its affiliates. This course is not affiliated with or endorsed by AWS.

Module details

Learn to process and query large datasets with AWS services like Redshift and Apache Spark. Master data workflows, performance optimization, and Redshift integrations, including ML and Lambda UDFs.

What's included

12 videos3 readings4 assignments

12 videosTotal 69 minutes

Course Introduction7 minutes
Getting Started with Redshift6 minutes
Understanding Redshift Spectrum6 minutes
Boosting Query Performance in Redshift7 minutes
Exploring RA3 Nodes and Cross-Region Sharing4 minutes
Data Handling with Redshift Workflows6 minutes
Demo:Redshift Walkthrough6 minutes
Understanding Redshift ML 5 minutes
Getting to Know Redshift Serverless7 minutes
Overview of Redshift Data API5 minutes
Overview of Apache Sparks 6 minutes
Integrating Spark with AWS Data Services6 minutes

3 readingsTotal 30 minutes

Understanding Redshift’s Data Distribution10 minutes
Understanding Redshift Lambda UDFs10 minutes
Exploring Redshift System Tables 10 minutes

4 assignmentsTotal 65 minutes

Introduction to Data Querying18 minutes
Advanced Data Processing21 minutes
Introduction to Data Querying12 minutes
Advanced Data Processing14 minutes

Dive into real-time data analytics with Kinesis, Athena, and AWS Glue for ETL tasks. Learn to process streaming data, scale real-time applications, and visualize data with QuickSight and MSK.

What's included

30 videos2 readings6 assignments

30 videosTotal 175 minutes

Intro to AWS Glue7 minutes
Mastering AWS Glue8 minutes
Understanding Glue Workflows6 minutes
Overview of Amazon Athena6 minutes
Athena: Optimize & Transact6 minutes
Demo:Athena + Glue5 minutes
Overview of Amazon EMR6 minutes
Understanding Amazon Kinesis Data Streams6 minutes
Understanding Kinesis Producers and Consumers5 minutes
Stream Scaling with Kinesis5 minutes
Handling Duplicates in Kinesis6 minutes
Securing Kinesis Data Streams5 minutes
Demo:Kinesis Data Stream7 minutes
Overview of Amazon Data Firehose7 minutes
Monitoring and Troubleshooting Kinesis Performance 6 minutes
Streaming Analytics with Kinesis Data Analytics and Flink7 minutes
Introduction to MSK 6 minutes
Understanding Amazon QuickSight7 minutes
Intro to OpenSearch 7 minutes
Understanding Open Search Index Management4 minutes
Overview of AWS AppFlow6 minutes
Understanding SQS6 minutes
Understanding SNS7 minutes
Demo:Creating a SQS Dead Letter Queue5 minutes
Demo:Sending Notification with SNS4 minutes
EventBridge Essentials5 minutes
Demo:AWS Eventbridge4 minutes
Amazon Managed Workflows for Apache Airflow6 minutes
Understanding AWS Step Functions8 minutes
Course Completion3 minutes

2 readingsTotal 20 minutes

Introduction to AWS lake formation10 minutes
Fan-Out in Kinesis: Concept and Use Cases 10 minutes

6 assignmentsTotal 126 minutes

Analytics for Data Engineering48 minutes
Streaming , Messaging Essentials and application integration30 minutes
AWS Glue and Amazon Athena10 minutes
Real-Time Data Streaming and Analytics with AWS Kinesis & Lake Formation22 minutes
Data Integration, Visualization, and Search with AWS Services8 minutes
Messaging Essentials and application integration8 minutes